Faculty publication

Research on Women’s Employment and COVID-19 by Professor Couch released by NBER

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“The Evolving Impacts of the COVID-19 Pandemic on Gender Inequality in the U.S. Labor Market:  The COVID Motherhood Penalty” has been released by the National Bureau of Economic Research as Working Paper 29426.

The paper is co-authored by Professor Ken Couch along with Robert Fairlie at the University of California Santa Cruz and Huanan Xu at Indiana University South Bend.

Abstract:

We explore whether COVID-19 disproportionately affected women in the labor market using CPS data through the end of 2020. We find that male-female gaps in the employment-to-population ratio and hours worked for women with school-age children have widened but not for those with younger children. Triple-difference estimates are consistent with most of the reductions observed for women with school-age children being attributable to additional child care responsibilities (the “COVID motherhood penalty”). Conducting decompositions, we find women had a greater likelihood to telework, higher education levels and a less-impacted occupational distribution, which all contributed to lessening negative impacts relative to men.

The paper can be found at this link:  https://www.nber.org/papers/w29426

Professor Agüero Publishes in the Journal of Development Economics

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Professor Jorge Agüero has published “The value of redistribution: Natural resources and the formation of human capital under weak institutions”  in the Journal of Development Economics.

The paper is coauthored with Carlos Felipe Balcázar, Stanislao Maldonado and Hugo Ñopo.

Abstract: We exploit time and spatial variation generated by the commodities boom to measure the effect of natural resources on human capital formation in Peru, a country with low governance indicators. Combining test scores from over two million students and district-level administrative data of mining taxes redistributed to local governments, we find sizable effects on student learning from the redistribution. However, and consistent with recent political economy models, the relationship is non-monotonic. Based on these models, we identify improvements in school expenditure and infrastructure, together with increases in health outcomes of adults and children, as key mechanisms explaining the effect we find for redistribution. Policy implications for the avoidance of the natural resource curse are discussed.

The paper may be found online at:

https://www.sciencedirect.com/science/article/abs/pii/S0304387820301565

Tales from My First 90 Years by Professor Emeritus Alpha Chiang

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Professor Emeritus Alpha Chiang has published a new book, Tales from My First 90 Years 

Alpha C Chiang, a renowned economist, and Professor Emeritus of Economics at the University of Connecticut, is best-known for his classic textbook — Fundamental Methods of Mathematical Economics.

In this memoir, he tells the entertaining, scary, embarrassing, glorifying and surreal tales that colored his life.

On the academic side, Alpha describes in detail his scholastic journey, including why and how he created one of the most popular books on mathematical methods in economics, as well as the experiences of his teaching career. On the nonacademic side, he describes his ventures into his many hobbies, the spices of his life, including Chinese opera, ballroom dancing, painting and calligraphy, photography, piano, music composition, playwriting, and even magic. Such tales round out the depiction of a colorful life.

https://www.worldscientific.com/worldscibooks/10.1142/11850

Alexander Vaninsky publishes in Environment Systems and Decisions

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Professor Alexander Vaninsky, a long-time economics instructor at the Stamford Campus, recently published the article “Multiobjective restructuring aimed at green economic growth” in Environment Systems and Decisions (February 2021) https://rdcu.be/ch3UZ

ABSTRACT

This research introduces an approach to the structural optimization of national economies resulting in green economic growth.  This study considers the comparative advantages of the sectors of the economy in the final product ratio, energy intensity, and carbonization of the gross output. The input–output model is transformed to a structured form, and the projected gradient of the gross domestic product (GDP) is derived. Factorial models of energy consumption and carbon dioxide (CO2) emissions are developed and used to obtain the projected antigradients of these indicators. Each of these vectors determine the locally

optimal structural change for each dimension. Their components are found to be proportional to the sectoral deviations from the national average, thus revealing a sectorwise comparative advantage or disadvantage. This observation allowed us to characterize these components as Ricardian gradients. Although it is not possible to move in each of the three vectors concurrently, it is possible to direct the economic restructuring to make the least possible acute angles with each vector.  Thus, the locally Pareto-optimal vector of structural change is formed. At each moment in time, the system is directed to move alongside this vector or by the boundary. The suggested approach is applied to simulate the economies of China and the United States. The obtained results reveal that the suggested changes in the structure of the gross output simultaneously allowed for an increase in GDP, a decrease in energy consumption, and the mitigation of CO2 emissions. Applications to international cooperation and trade are discussed.

 

Professor Agüero Publishes in World Development

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Professor Jorge Agüero has published his paper “COVID-19 and The Rise of Intimate Partner Violence” in World Development

The paper may be found online at: https://doi.org/10.1016/j.worlddev.2020.105217

The abstract is below:

Title: COVID-19 and The Rise of Intimate Partner Violence

Abstract: Stay-at-home policies have been implemented worldwide to reduce the spread of the SARS-CoV-2 virus. However, there is a growing concern that such policies could increase violence against women. We find evidence in support of this critical concern. We focus on Peru, a country that imposed a strict nationwide lockdown starting in mid-March and where nearly 60% of women already experienced violence before COVID-19. Using administrative data on phone calls to the helpline for domestic violence (Línea 100), we find that the incidence rate of the calls increased by 48 percent between April and July 2020, with effects increasing over time. The rise in calls is found across all states and it is not driven by baseline characteristics, including previous prevalence of violence against women. These findings create the need to identify policies to mitigate the negative impact of stay-at-home orders on women’s safety.

Professor Prakash publishes in Journal of Economics Behavior & Organization

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Professor Prakash publishes his paper on “Impact of Affirmative Action in Public Sector Employment on Lives of Disadvantaged Minorities in India” in Journal of Economics Behavior & Organization.

Title: The Impact of Employment Quotas on the Economic Lives of Disadvantaged Minorities in India

Abstract: India has the world’s biggest and arguably most aggressive employment-based affirmative action policy for minorities. This paper exploits the institutional features of a federally mandated employment quota policy to examine its causal impact on the economic lives of the two distinct minority groups (Scheduled Castes and Scheduled Tribes).

My main finding is that a 1-percentage point increase in the employment quota for Scheduled Castes increases the likelihood of obtaining a salaried job by 0.6-percentage points for male Scheduled Caste members residing in the rural sector. The employment quota policy has no impact for Scheduled Tribes. Contrary to popular notion, I do not find evidence of “elite-capture” among the Scheduled Castes — the impact is concentrated among members who have completed less than secondary education.

Consistent with the employment results, I find that the policy improved the well-being of Scheduled Castes members in rural areas who have completed less than secondary education. Finally, the impact of the employment quota policy varies by state characteristics.

Professor Hwang to publish “A Doubly Corrected Robust Variance Estimator for Linear GMM” in the Journal of Econometrics

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Professor Jungbin Hwang has had his article A Doubly Corrected Robust Variance Estimator for Linear GMM accepted for publication in the Journal of Econometrics, one of the top scholarly journals in theoretical econometrics.

The paper proposes a new finite sample corrected variance estimator for the linear generalized method of moments (GMM) including the one-step, two-step, and iterated estimators. The formula additionally corrects for the over-identification bias in variance estimation on top of the commonly used finite sample correction of Windmeijer (2005) which corrects for the bias from estimating the efficient weight matrix, so is doubly corrected. An important feature of the proposed double correction is that it automatically provides robustness to misspecification of the moment condition. In contrast, the conventional variance estimator and the Windmeijer correction are inconsistent under misspecification. That is, the proposed double correction formula provides a convenient way to obtain improved inference under correct specification and robustness against misspecification at the same time.

This article, authored with with Seojeong Lee (UNSW) and Byunghoon Kang (Lancaster Univ), is one of two that Professor Hwang has recently had accepted for publication. Details of the other article may be found at:

Professor Jungbin Hwang publishes “Simple and Trustworthy Cluster-Robust GMM Inference” in the Journal of Econometrics

Professor Jungbin Hwang publishes “Simple and Trustworthy Cluster-Robust GMM Inference” in the Journal of Econometrics

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Professor Jungbin Hwang has had his article Simple and Trustworthy Cluster-Robust GMM Inference accepted for publication in the Journal of Econometrics, a top field-journal in econometrics.

This paper develops a new asymptotic theory for GMM estimation and inference in the presence of clustered dependence. The key feature of the alternative asymptotic is that the number of clusters is regarded as “fixed” as the sample size increases. The paper shows that the Wald and t-tests in two-step GMM are asymptotically pivotal only if one recenters the estimated moment process in the clustered covariance estimator (CCE). Also, the J statistic, the trinity of two-step GMM statistics (QLR, LM, and Wald), and the t statistic can be modified to have an asymptotic standard F distribution or t distribution.

The paper also first suggests a finite-sample variance correction in the literature of cluster-robust methods and further improves the F and t approximations’ accuracy. The proposed tests in this paper are very appealing to practitioners because the test statistics are simple modifications of conventional GMM test statistics, and critical values are readily available from F and t tables without any extra simulations or resampling steps.

This sole authored article is one of two that Professor Hwang has recently had accepted for publication. Details of the other article may be found at:

Professor Hwang to publish “A Doubly Corrected Robust Variance Estimator for Linear GMM” in the Journal of Econometrics

Professor Couch Publishes in Journal of Public Economics

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Professor Kenneth Couch and his co-authors, Robert Fairlie (California Santa Cruz) and Huanan Xu (Indiana University South Bend) have published an article “Early Evidence of the Impact of COVID-19 on Minority Employment” In the Journal of Public Economics.

Article Abstract:

This paper provides early evidence of the impacts of the COVID-19 pandemic on minority unemployment in the United States. In the first month following March adoptions of social distancing measures by states, unemployment rose to 14.5 percent but a much higher 24.4 percent when we correct for potential data misclassification noted by the BLS. Using the official definition, unemployment in April 2020 among African-Americans rose by less than what would have been anticipated (to 16.6 percent) based on previous recessions, and the long-term ordering of unemployment across racial/ethnic groups was altered with Latinx unemployment (18.2 percent) rising for the first time to the highest among major groups. Difference-in-difference estimates confirm that the initial gap in unemployment between whites and blacks in April was not different than in periods prior to the pandemic; however, the racial gap expanded as unemployment for whites declined in the next two months but was largely stagnant for blacks. The initially large gap in unemployment between whites and Latinx in April was sustained in May and June as unemployment declined similarly for both groups. Non-linear decompositions show a favorable industry distribution partly protected black employment during the early stages of the pandemic, but that an unfavorable occupational distribution and lower average skills levels placed them at higher risk of job losses. An unfavorable occupational distribution and lower skills contributed to a sharply widened Latinx-white unemployment gap that moderated over time as rehiring occurred. These findings of disproportionate impacts on minority unemployment raise important concerns regarding lost earnings and wealth, and longer-term consequences of the pandemic on racial inequality in the United States.

The early release version of this article can be found at this link:

https://www.sciencedirect.com/science/article/pii/S0047272720301511

Professor Agüero publishes in Economic Development and Cultural Change

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Professor Jorge Agüero’s paper “Measuring Violence Against Women with Experimental Methods” has been accepted for publication by Economic Development and Cultural Change

The working paper may be found online at: https://ideas.repec.org/p/uct/uconnp/2020-14.html

Title: Measuring Violence Against Women with Experimental Methods
Authors: Jorge Aguero and Veronica Frisancho

Abstract: The prevalence of intimate partner violence is a central indicator of the Sustainable Development Goals for women’s agency. However, measuring this indicator largely relies on self-reports that could suffer from severe misreporting if women face high costs of revealing their victim status. We study the degree of misreporting in surveys that have been identified as the best source of data, such as the widely used Demographic and Health Surveys (DHS). Focusing on a sample of women in impoverished urban areas of Lima, Peru, we conduct an experiment that replicates direct measures from these surveys and compares them against list experiments, a method that provides greater privacy to respondents. We find no significant differences across direct and indirect methods in any of the seven acts of physical and sexual violence considered. This result largely persists when testing across sixteen different subgroups and accounting for multiple hypothesis testing.